Dr. Downing has been up to some very interesting things with Nova lately, devising a “genetic algorithm” model for Nova that can be integrated with most types of agents, such that a user-chosen set of properties can be evolved. He is also developing a “neural net” model for Nova that can convert agents’ sensory information to motor output commands for the agent through a neural network.

Prior work on such models has been established by Dr. Wayne Getz, who implemented both of these models in a Nova example, and Dr. Richard Salter who has authored backpropagation neural networks for Nova. According to Dr. Downing, “The main difference is that I’m trying to put together a few general tools that a Nova user could hook into their own model.” He also, explains that the networks that Dr. Salter has implemented are aimed at a type of machine learning scenario called classification. Dr. Downing’s models are more intended for artificial life scenarios, whereas Dr. Salter’s models are more directed toward connectionist artificial intelligence scenarios.

Dr. Downing’s Nova models will be available soon. In the meantime, fortunately we at Nova found a highly intriguing, accessible, and entertaining presentation by Dr. Downing that explains theoretical and historical links between evolutionary computation, emergence, nature, and artificial life applications ranging from the game Battleship to Nazi war codes, Mars rovers to driverless automobiles, and evolutionary art to evolutionary robotics.